Please wait a minute...
浙江大学学报(工学版)
浙江大学学报(工学版)  2022, Vol. 56 Issue (5): 843-855    DOI: 10.3785/j.issn.1008-973X.2022.05.001
机械工程     
面向可重构制造的数字孪生映射建模与监控仿真
冷柏寒1,2(),夏唐斌1,2,*(),孙贺1,2,王皓1,2,奚立峰1,2
1. 上海交通大学 机械与动力工程学院，机械系统与振动国家重点实验室，上海 200240
2. 上海交通大学弗劳恩霍夫智能制造项目中心，上海 201306
Digital twin mapping modeling and method of monitoring and simulation for reconfigurable manufacturing system
Bo-han LENG1,2(),Tang-bin XIA1,2,*(),He SUN1,2,Hao WANG1,2,Li-feng XI1,2
1. State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2. Fraunhofer Project Center for Smart Manufacturing at Shanghai Jiao Tong University, Shanghai 201306, China
 全文: PDF(1929 KB)   HTML
摘要：

针对数字孪生在可重构制造系统（RMS）的应用问题，提出面向RMS的数字孪生与制造仿真一体化平台（DTMSIP）架构. DTMSIP架构充分适配RMS动态重构特性，可以在RMS构型设计中实现仿真分析. 对面向RMS的数字孪生映射进行建模，通过引入孪生实体（TE），实现RMS车间的多源异构数据集成，并分别建立机床与构型的数字孪生映射. 建立数字孪生方法在RMS重构中的应用流程，通过信息物理融合迭代与构型仿真优化迭代，DTMSIP可以服务于RMS的系统重构. 为了验证所提出方法的可行性，使用虚幻引擎四（UE4）为一套实际的模块化RMS构建数字孪生平台，并将当前构型以及4种规划构型作为仿真输入. 通过分析重构成本、生产周期与系统平衡率3项指标，实现对构型的量化综合分析，实现了重构设计流程加速.
关键词： 数字孪生;  可重构制造系统;  映射建模;  实时仿真;  系统重构    
Abstract:

Digital twin and manufacturing simulation integrated platform (DTMSIP) architecture for reconfigurable manufacturing system (RMS) was proposed, aiming at the application problem of digital twin on RMS. DTMSIP was highly adapted to RMS’s dynamic reconfiguration and can be used for simulation analysis in RMS configuration design. Digital twin mapping for RMS was modeled. By defining twinning entity (TE), heterogeneous multi-source data integration in RMS shop-floor was realized and digital twin mapping for machine tools and configuration was established. The application procedure of digital twin-based RMS reconfiguration was proposed. DTMSIP served the purpose of assisting RMS reconfiguration through iteration of cyber physical fusion and iteration of configuration simulation. In order to validate the proposed method, Unreal Engine 4 (UE4) was adopted to implement DTMSIP software for a modular RMS. Current configuration and four planned configurations were input to DTMSIP software for simulation. Quantitative and comprehensive analysis was performed on the configurations taking into consideration cost of reconfiguration, cycle time and line balance, contributing to accelerate RMS reconfiguration design processes.
Key words: digital twin    reconfigurable manufacturing system    mapping modeling    real-time simulation    system reconfiguration
收稿日期: 2021-10-20 出版日期: 2022-05-31
CLC:  TH 181  
基金资助: 国家自然科学基金资助项目(51875359)；上海市“科技创新行动计划”自然科学基金资助项目(20ZR1428600)；上海商用飞机系统工程科创中心联合研究基金资助项目(FASE-2021-M7)；教育部-中国移动联合基金建设项目(MCM20180703)；上海交通大学深蓝计划基金资助项目(SL2021MS008)；中船-交大海洋装备前瞻创新基金(22B010432)
通讯作者: 夏唐斌     E-mail: lamberhand@gmail.com;xtbxtb@sjtu.edu.cn
作者简介: 冷柏寒 （1997—），男，硕士生，从事数字孪生技术与可重构制造研究. orcid.org/0000-0002-5199-5939. E-mail: lamberhand@gmail.com
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章　　
冷柏寒
夏唐斌
孙贺
王皓
奚立峰

引用本文:

冷柏寒,夏唐斌,孙贺,王皓,奚立峰. 面向可重构制造的数字孪生映射建模与监控仿真[J]. 浙江大学学报(工学版), 2022, 56(5): 843-855.

Bo-han LENG,Tang-bin XIA,He SUN,Hao WANG,Li-feng XI. Digital twin mapping modeling and method of monitoring and simulation for reconfigurable manufacturing system. Journal of ZheJiang University (Engineering Science), 2022, 56(5): 843-855.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2022.05.001    或    https://www.zjujournals.com/eng/CN/Y2022/V56/I5/843

图 1  面向可重构制造的数字孪生与制造仿真一体化平台架构
孪生实体类型 工况表征值 孪生数据源 数据传输方法 数字孪生表现方法
布尔状态孪生实体 {True, False} RFID、I/O寄存器、PLC Modbus、RTDE、TCP/IP、CPS API 运动、碰撞体阻挡或放行
枚举状态孪生实体 SetTE PLC、上位机软件状态判定 Modbus、RTDE、TCP/IP、CPS API 运动、UI图标
数值变量孪生实体 ValTE 机器人控制、PLC Modbus、RTDE、TCP/IP、CPS API 运动、数据看板
表 1  基于孪生实体的机床行为映射方法
图 2  基于DTMSIP的RMS重构流程
图 3  面向RMS的通用T型机床底座
图 4  可重构制造系统构型解析
图 5  当前系统构型及待仿真验证的4种规划构型
图 6  当前构型实际生产与生产仿真甘特图
仿真构型 $ C_{{\text{Rec}}}^\prime $构成 $ C_{{\text{Rec}}}^\prime $/CNY ${T_{{\text{Bat}}}}$/s ${\text{Bal}}$/%
当前构型 ? ? 518.1 51.3
规划构型① ${\text{PI} }({M^{\rm{F}}}) + P({\text{Base} })$ 280 000 476.4 63.0
规划构型② ${\text{PI} }({M^{\rm{F}}}) + {\text{PI} }({M^{{\rm{A}}/{\rm{G}}} }) + 2P({\text{Base} })$ 420 000 449.9 63.0
规划构型③ ${\text{PI} }({M^{\rm{F}}}) + {\text{PI} }({M^{{\rm{A}}/{\rm{G}}} }) + 2P({\text{Base} })$ 420 000 451.6 63.0
规划构型④ ${\text{PI} }({M^{\rm{F}}}) + {\text{PI} }({M^{\rm{E}}}) + {\text{PI} }({M^{{\rm{A}}/{\rm{G}}} }) + 3P({\text{Base} })$ 820 000 419.9 77.4
表 2  4种规划构型仿真结果
图 7  采纳的规划构型①的生产仿真与实际生产甘特图
1 陶飞, 刘蔚然, 刘检华, 等 数字孪生及其应用探索[J]. 计算机集成制造系统, 2018, 24 (1): 1- 18
TAO Fei, LIU Wei-ran, LIU Jian-hua, et al Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing Systems, 2018, 24 (1): 1- 18
2 陶剑, 戴永长, 魏冉 基于数字线索和数字孪生的生产生命周期研究[J]. 航空制造技术, 2017, 21: 26- 31
TAO Jian, DAI Yong-chang, WEI Ran Study on production lifecycle based on digital thread and digital twin[J]. Aeronautical Manufacturing Technology, 2017, 21: 26- 31
3 LU Y, LIU C, WANG K, et al Digital twin-driven smart manufacturing: connotation, reference model, applications and research issues[J]. Robotics and Computer-integrated Manufacturing, 2020, 61: 101837
4 郑守国, 张勇德, 谢文添, 等 基于数字孪生的飞机总装生产线建模[J]. 浙江大学学报: 工学版, 2021, 55 (5): 843- 854
ZHENG Shou-guo, ZHANG Yong-de, XIE Wen-tian, et al Aircraft final assembly line modeling based on digital twin[J]. Journal of Zhejiang University: Engineering Science, 2021, 55 (5): 843- 854
5 丁凯, 张旭东, 周光辉, 等 基于数字孪生的多维多尺度智能制造空间及其建模方法[J]. 计算机集成制造系统, 2019, 25 (6): 1491- 1504
DING Kai, ZHANG Xu-dong, ZHOU Guang-hui, et al Digital twin-based multi-dimensional and multi-scale modeling of smart manufacturing spaces[J]. Computer Integrated Manufacturing Systems, 2019, 25 (6): 1491- 1504
6 ZHANG C, XU W, LIU J, et al A reconfigurable modeling approach for digital twin-based manufacturing system[J]. Procedia CIRP, 2019, 83: 118- 125
7 程浙武, 童水光, 童哲铭, 等 工业锅炉数字化设计与数字孪生综述[J]. 浙江大学学报: 工学版, 2021, 55 (8): 1518- 1528
CHENG Zhe-wu, TONG Shui-guang, TONG Zhe-ming, et al Review of digital design and digital twin of industrial boiler[J]. Journal of Zhejiang University: Engineering Science, 2021, 55 (8): 1518- 1528
8 陶飞, 张萌, 程江峰, 等 数字孪生车间: 一种未来车间运行新模式[J]. 计算机集成制造系统, 2017, 23 (1): 1- 9
TAO Fei, ZHANG Meng, CHENG Jiang-feng, et al Digital twin workshop: a new paradigm for future workshop[J]. Computer Integrated Manufacturing Systems, 2017, 23 (1): 1- 9
9 江海凡, 丁国富, 张剑 数字孪生车间演化机理及运行机制[J]. 中国机械工程, 2020, 31 (7): 824- 832
JIANG Hai-fan, DING Guo-fu, ZHANG Jian Evolution and operation mechanism of digital twin shopfloors[J]. China Mechanical Engineering, 2020, 31 (7): 824- 832
doi: 10.3969/j.issn.1004-132X.2020.07.008
10 TAO F, QI Q, WANG L, et al Digital twins and cyber-physical systems toward smart manufacturing and industry 4.0: correlation and comparison[J]. Engineering, 2019, 5 (4): 653- 661
11 YILDIZ E, MØLLER C, BILBERG A Virtual factory: digital twin based integrated factory simulations[J]. Procedia CIRP, 2020, 93: 216- 221
12 LENG B, SUN H, SI G, et al Digital twin and manufacturing simulation integrated platform embedded in cyber-physical system[J]. Journal of Physics: Conference Series, 2021, 1983 (1): 012117
13 KOREN Y, HEISEL U, JOVANE F, et al Reconfigurable manufacturing systems[J]. CIRP Annals, 1999, 48 (2): 527- 540
14 KOREN Y, SHPITALNI M Design of reconfigurable manufacturing systems[J]. Journal of Manufacturing Systems, 2010, 29 (4): 130- 141
15 YANG C, GAO J, SUN L A multi-objective genetic algorithm for mixed-model assembly line rebalancing[J]. Computers and Industrial Engineering, 2013, 65 (1): 109- 116
16 BRYAN A, HU S J, KOREN Y Assembly system reconfiguration planning[J]. Journal of Manufacturing Science and Engineering, 2013, 135 (4): 041005
17 王青, 温李庆, 李江雄, 等 基于Petri网的飞机总装配生产线建模及优化方法[J]. 浙江大学学报: 工学版, 2015, 49 (7): 1224- 1231
WANG Qing, WEN Li-qing, LI Jiang-xiong, et al Modeling and optimization for aircraft final assembly line based on Petri net[J]. Journal of Zhejiang University: Engineering Science, 2015, 49 (7): 1224- 1231
18 MICHALOS G, FYSIKOPOULOS A, MAKRIS S, et al Multi criteria assembly line design and configuration: an automotive case study[J]. CIRP Journal of Manufacturing Science and Technology, 2015, 9: 69- 87
19 ROSEN R, VON WICHERT G, LO G, et al About the importance of autonomy and digital twins for the future of manufacturing[J]. IFAC-Papers OnLine, 2015, 48 (3): 567- 572
20 YELLES-CHAOUCHE A R, GUREVSKY E, BRAHIMI N, et al Reconfigurable manufacturing systems from an optimisation perspective: a focused review of literature[J]. International Journal of Production Research, 2021, 59 (21): 6400- 6418
21 GANSTERER M, ALMEDER C, HARTL R F Simulation-based optimization methods for setting production planning parameters[J]. International Journal of Production Economics, 2014, 151: 206- 213
22 GOLA A Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods[J]. Eksploatacja I Niezawodność, 2019, 21 (1): 90- 102
23 PETROODI S, EYNAUD A, KLEMENT N, et al Simulation-based optimization approach with scenario-based product sequence in a reconfigurable manufacturing system (RMS): a case study[J]. IFAC-PapersOnLine, 2019, 52 (13): 2638- 2643
24 CENTOBELLI P, CERCHIONE R, MURINO T Layout and material flow optimization in digital factory[J]. International Journal of Simulation Modelling, 2016, 15 (2): 223- 235
25 ZHANG H, LIU Q, CHEN X, et al A digital twin-based approach for designing and multi-objective optimization of hollow glass production line[J]. IEEE Access, 2017, 5: 26901- 26911
26 CAI Y, WANG Y, BURNETT M Using augmented reality to build digital twin for reconfigurable additive manufacturing system[J]. Journal of Manufacturing Systems, 2020, 56: 598- 604
27 LENG J, LIU Q, YE S, et al Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model[J]. Robotics and Computer-integrated Manufacturing, 2020, 63: 101895
28 BAHETI R, GILL H Cyber-physical systems[J]. The Impact of Control Technology, 2011, 12 (1): 161- 166
29 WEYER S, MEYER T, OHMER M, et al Future modeling and simulation of CPS-based factories: an example from the automotive industry[J]. IFAC-PapersOnLine, 2016, 49 (31): 97- 102
30 XIA T, XI L, PAN E, et al Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems[J]. Reliability Engineering and System Safety, 2017, 166: 87- 98
[1] 李琳利,顾复,李浩,顾新建,罗国富,武志强,刚轶金. 仿生视角的数字孪生系统信息安全框架及技术[J]. 浙江大学学报(工学版), 2022, 56(3): 419-435.
[2] 程浙武,童水光,童哲铭,张钦国. 工业锅炉数字化设计与数字孪生综述[J]. 浙江大学学报(工学版), 2021, 55(8): 1518-1528.
[3] 郑守国,张勇德,谢文添,樊虎,王青. 基于数字孪生的飞机总装生产线建模[J]. 浙江大学学报(工学版), 2021, 55(5): 843-854.
[4] 余小勇,魏燕定,黄茫茫,周晓军,杨辰龙. 基于HLA的车辆半实物仿真中精确定时方法[J]. J4, 2012, 46(7): 1195-1200.